Severity of underweight and risk of fracture: a Korean nationwide population-based cohort study

Underweight is an important modifiable risk factor for fractures. However, there have been few large cohort studies regarding the relationship between underweight and fracture in the general population. We investigated the risk of fracture development according to underweight severity in a large population cohort. This nationwide cohort study included 2,896,320 people aged ≥ 40 years who underwent national health checkups in 2009 and were followed up to identify the incidence of fracture until December 31, 2018. After applying the exclusion criteria that included overweight and obese individuals, the study population was divided according to body mass index (BMI) into normal weight (18.5 ≤ BMI < 23.0), mild underweight (17.5 ≤ BMI < 18.5), moderate underweight (16.5 ≤ BMI < 17.5), and severe underweight (BMI < 16.5) groups. Cox proportional hazards regression analyses were performed to calculate the hazard ratios for risk of fracture according to underweight severity. Severely underweight participants had a 28% increased fracture risk (adjusted hazard ratio [HR] 1.28, 95% confidence interval [CI] 1.20–1.37) compared with those of normal weight. In addition, fracture risk was increased by 14% in individuals with moderate underweight (adjusted HR 1.14, 95% CI 1.08–1.19) and 9% in those with mild underweight (adjusted HR 1.09, 95% CI 1.06–1.13). The severity of underweight was significantly associated with risk of fracture.


Incidence of fracture.
To confirm the causes of all fracture cases, we used ICD-10 codes and hospitalization records from the NHIS system. Fractures were defined using the ICD-10 codes as follows: vertebral fractures (S12.0, S12.1, S12. Covariates. The NHIS database includes data on demographics, socioeconomic status, comorbidities, and laboratory findings, such as total cholesterol level, blood glucose level, and estimated glomerular filtration rate. Participants were classified according to smoking status as non-smokers, ex-smokers, or current smokers. Participants were classified according to alcohol consumption as non-drinkers, moderate drinkers (< 30 g/day), or heavy drinkers (≥ 30 g/day) 16 . Regular exercise was defined as at least 20 min of high-intensity physical activity ≥ 3 days per week or at least 30 min of moderate-intensity physical activity ≥ 5 days per week 17 . Low income was defined as an income < 20th percentile.
Diabetes was defined as a fasting blood sugar level > 126 mg/dL or prescription of an antidiabetic agent (ICD-10 codes, E11-E14). Hypertension was defined as an average blood pressure ≥ 140/90 mmHg, or more than one annual prescription of an antihypertensive agent (ICD-10 codes, I10-I13 or I15). Dyslipidemia was defined as a total cholesterol level ≥ 240 mg/dL or more than one annual prescription of an antihyperlipidemic agent (ICD-10 code, E78). Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate < 60 mL/ min/1.73 m 2 . Previous studies validated the definitions of comorbidities based on the ICD codes 15,18 . Statistical analysis. Statistical analyses were performed using the chi-squared test for categorical variables and analysis of variance (ANOVA) for continuous variables. The incidence rate (IR) was calculated by dividing the outcome rate per 1000 person-years (PY) by the total number of fractures. The 95% confidence intervals (CIs) and hazard ratios (HRs) for fractures based on underweight severity were calculated using Cox regression analysis. We constructed a hierarchical model with different levels of demographic, socioeconomic factors, and comorbidities to investigate covariates potentially affecting fracture risk: model 1 was non-adjusted; model 2 was adjusted for age and sex; model 3 was additionally adjusted for other factors, including alcohol consumption, smoking status, low income, and regular exercise; and model 4 was fully adjusted with additional adjustments for comorbidities such as diabetes, hypertension, dyslipidemia, and CKD. We also compared the cumulative incidences of fractures between groups using the Kaplan-Meier method. To examine the effects of clinical conditions on the association between risk of fracture and underweight severity, the HRs for fractures in diverse subgroups were determined by Cox proportional hazards regression analysis and P values for interaction. Stratified subgroup analysis was performed based on age (< 65 and ≥ 65 years old), sex, smoking status, alcohol consumption, household income, regular activity, and comorbidities. All statistical analyses were performed using SAS software (ver. 9.3; SAS Institute, Cary, NC, USA). A two-sided P < 0.05 was taken to indicate statistical significance. consent requirement was waived because the data analyses were performed retrospectively using anonymous data derived from the NHIS database in Korea. This study was also approved by the institutional review board of Korea University Ansan Hospital, Republic of Korea (approval no. K2021-2601-001). All research processes were conducted in accordance with the appropriate regulations and guidelines, and this study was performed in accordance with the provisions of the Declaration of Helsinki.

Results
A total of 2,896,320 adults over the age of 40 years underwent NHIS-provided health check-ups in Korea in 2009. A total of 102,612 individuals were excluded due to missing data on variables, 244,328 were excluded due to previous fractures before study enrollment, and 34,302 were excluded due to a fracture occurring during the 1-year lag period. In addition, 1,552,545 overweight or obese individuals were also excluded. Finally, 962,533 subjects were included in the analysis (Fig. 1).

Baseline characteristics.
A descriptive overview of the participants' characteristics according to underweight severity is presented in Table 1

Severity of underweight and fracture. Cox proportional hazards regression analyses were performed
to determine the risk of fracture in participants according to underweight severity ( Table 2). The normal weight group served as the reference for fracture events. Participants with severe underweight showed markedly higher risks of subsequent fracture, despite adjustments for several potential confounders (adjusted HR 1.28, 95% CI 1.20-1.37). The Kaplan-Meier curves for each group are shown in Fig. 2, and the results showed a significantly higher fracture incidence in the severe underweight group than in the other groups at all time points (log-rank test, P < 0.001).
Subgroup analysis. Subgroup analyses were performed by stratifying the study population according to age, sex, smoking status, alcohol consumption, low income, and comorbidities. The adjusted fracture risks according to underweight severity in each subgroup are presented in Table 3. The association between underweight severity and fracture risk was similar across the subgroups. In the subgroups of age > 65 years, male sex, hypertension, and diabetes, severe underweight had a greater effect on fracture risk. No significant differences were observed in the other subgroup analyses of fracture risk according to smoking status, alcohol consumption, low income, dyslipidemia, and CKD (P > 0.05).

Discussion
The present study was performed to investigate the association between underweight severity and the development of fracture in a nationwide general population in Korea. Underweight was subdivided into mild (17.5 ≤ BMI < 18.5), moderate (16.5 ≤ BMI < 17.5), and severe underweight (BMI < 16.5). The risk of fracture increased in proportion to underweight severity, with severely underweight individuals showing the highest fracture risk in the general population. To our knowledge, this is the first study to examine the association between underweight severity and fracture risk using real-world large population-based data. Similar to our findings, previous studies reported that underweight is associated with fracture risk 19,20 This association may be explained by the following hypotheses. First, lower body weight is associated with less soft tissue, including around the bones. As subcutaneous fat can act as a buffer against damage, it is advantageous for maintenance of bone structure and strength 21 . Second, underweight is associated with low bone mineral density. This association can be explained by the gravitational effect of body weight on bones, along with the effects of body fat and lean body mass 6,22 . Third, underweight may be associated with deficiencies in nutrients, such as vitamin D and protein 23 . Low vitamin D levels has been shown to be associated with defective mineralization of collagenous matrix (osteoid) 24 , and protein depletion may affect the bone remodeling process by reducing the www.nature.com/scientificreports/ production of insulin-like growth factor 1 25 . Fourth, Gariballa et al. reported a significantly increased prevalence of sarcopenia in underweight patients compared with those with normal or increased body weight 4 . Decreased muscle mass may not provide adequate bone protection, and reduced muscle strength may increase the risk of fall-related injuries 26,27 .
In the present study, older underweight subjects (≥ 65 years) showed a greater fracture risk compared with younger subjects (< 65 years). A previous study showed that underweight in the elderly was associated with malnutrition and osteoporosis, both of which are risk factors for fracture 23 . Comorbidities may be associated with the occurrence of fractures, and in the present study, participants with high blood pressure or diabetes also had a higher fracture risk. Hypertension can cause long-term impairment of calcium homeostasis, resulting in persistent calcium loss in the urine, which increases the rate of mineral loss 28 . In addition, high blood pressure is associated with a high level of parathyroid hormone, which can accelerate bone turnover and decrease bone mass 29 . Metabolic effects of diabetes, such as acidosis and hypercalcemia, may increase the risk of fractures 30 .
Our results may have important implications from a clinical and public health perspective, supporting the need to avoid severe underweight in adults over 40 years of age and to avoid becoming severely underweight to reduce the risk of fractures. Although our data could not show that the risk of fractures is reduced when severe  A notable strength of this study is that our results can be generalized to the Korean population because we used large-scale population-based data representing the whole country to analyze the relationship between underweight severity and fracture risk. However, this study had some limitations. First, our findings could not determine causal relationships due to its retrospective design. In addition, we attempted to adjust for possible confounding factors, but it is possible that some confounders remained. Second, we could not take bone mineral density into consideration because of a lack of relevant information in the NHIS database. Third, we could not determine the cause of the fracture. In the NIHS database, there was insufficient information on injury mechanisms or laboratory findings to determine the cause of fractures. Further well-designed prospective studies are needed to overcome these limitations.

Conclusion
Underweight severity was shown to be associated with fracture risk in the general Korean population. Individuals who were more severely underweight had a higher risk of fractures. In particular, the risk of fracture was significantly higher in men than in women, individuals ≥ 65 years than in those < 65 years, and subjects with hypertension and diabetes than in those without these comorbidities.